Sustainability Metrics
Secondary Data

Chris Donovan

Food Systems Research Center

March 19, 2025

Introduction

Goals for secondary data:
- Identify existing data and gaps
- Explore methods of aggregating data
Structure of presentation:
1. Framework and methods
2. Preliminary results of case study
3. Uncertainty and sensitivity
Guiding questions:
- How well do the data represesent the system?
- Valuation, scaling, weighting, aggregation
- Where and how do we incorporate qualitative data?

Findings:
- Gaps in secondary data
  - Soil health, carbon stocks, water quantity
  - Food distribution, loss, and waste
  - Diversity of farm types, production diversity
  - Social dimension
- Framework complexity and coherence
- Stability and sensitivity
- Influential indicators
Looking ahead:
- Find more info on metrics and analysis at the Sustainability Metrics methods website
- Sustainability Metrics repository

Gaps:
- NASS stats lean toward commodity crops
- Soil health
- Food distribution capacity (have some of this)
- Food loss and waste
- Embodied Carbon
- Carbon stocks
- forest complexity
- water quality
- water quantity
- precarity, market health indices
- diversity of Farm Types (this one tricky for VT)
- nutrition*
- all of social dimension*
Complexity and coherence:
- Cronbach: Some are coherent (health, and lesser extent economics and environment)
- Is this important to us? What does this mean for social dimension?
Sensitivity:
- Some dimensions stable (health)
- Others ambiguous (economics)
- Metric counts: fewer means risk of poor fit
- Diagnostic for indicator influence (production species diversity)
Metric counts: fewer increases risks?
Influential indicators:
- Carbon fluxes (10 interactions)
- Access to care, value added market (6)
- Operations diversification, phyiscal health, production quantities (5)
- More about GDP? Need to deal with this
- Social connectedness (5)
- From indicator sensitivity: social connectedness and production diversity